The QP Expression is a robotic colony picking and library management system that allows automated manipulation of bacterial or yeast clones, and RNAi libraries. The attributes of this system include software and programming capabilities involved in the generation, management, and use of complex libraries. For example, this system can take up varying volumes of transformation mixes and spread each sample onto user-defined grids. After growth, the instrument can recognize and pick colonies based on user definitions of size, shape, color, and proximity to neighboring clones. The picked colonies can then be arrayed into additional plates for purification, and rearrayed into multiwell dishes for generation of strain stocks. Clones can also be replicated into additional multiwell dishes or onto membranes for a variety of analyses of phenotype, including growth properties, protein production, and recognition by antibody or DNA probes. Through each step, the system tracks the source and destination of each clone, and allows the user to simply load the machine, program the software, and walk away. Similarly, particular RNAi clones/oligo sets can be tested and rearrayed for secondary screening. The QP Expression robot will save weeks of tedious labor currently performed by students, fellows and staff. Importantly, the automated tracking and cherry- picking attributes minimizes error and accelerates secondary and tertiary screens. The QP Expression instrument will support eight investigators at the Medical College of Wisconsin, who are Principal Investigators on 25 NIH-funded projects involved in the generation, screening, and analyses of libraries. In addition, this instrument will support the research of two additional investigators at neighboring institutions: the Great Lakes Water Institute at the University of Wisconsin-Milwaukee, and Marquette University. Each of these projects is relevant to human health. Projects include but are not limited to, the identification of bacteria in various mammalian "biomes" and water supplies, the identification of bacterial virulence factors, and the use of genomic approaches to map genetic determinants relevant to a variety of human diseases. We anticipate that as the instrument comes on line, the number of users will increase and the types of applications will expand. For example, we can anticipate the investigators seeking to analyze the structure and function of proteins might want to apply random mutagenesis approaches and an automated screen. Further, as derivatives are identified and analyzed biologically, we anticipate feeding these directly into our structural biology core, which possesses automated systems for obtaining protein crystals. At present, there is no high-throughput instrument to facilitate progress on these diverse studies. The QP Expression system will complement existing systems on the College campus and facilitate the research supported by more than $8,274,000 in current NIH funding.